CN108182511A - It is a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method - Google Patents

It is a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method Download PDF

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CN108182511A
CN108182511A CN201711308652.1A CN201711308652A CN108182511A CN 108182511 A CN108182511 A CN 108182511A CN 201711308652 A CN201711308652 A CN 201711308652A CN 108182511 A CN108182511 A CN 108182511A
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sum
ranks
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王燕
王俊伟
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Shanghai University of Electric Power
University of Shanghai for Science and Technology
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Abstract

The present invention relates to a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method, include the following steps：1st, the evaluating matrix of multiple evaluation indexes of multiple assessment objects is established；2nd, each assessment object corresponding to evaluation index each in evaluating matrix compiles order, and the sum of ranks ratio of assessment object is calculated；3rd, the downward cumulative frequency of each assessment object is calculated and is converted into probability unit；4th, using probability unit as independent variable, regression equation is established as dependent variable using the sum of ranks ratio for assessing object；5th, grading sorting is carried out to assessment object according to regression equation, obtains evaluation result.Compared with prior art, the present invention considers index weights on the basis of traditional RSR methods, effectively avoid the subjectivity that multifactor weight determines, not only the sum of ranks ratio that the Leakage in Value of Demand Side Response resource is evaluation object can also be carried out grading sorting to the value of Demand Side Response resource.

Description

It is a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method
Technical field
The present invention relates to electricity markets and economic field, are provided more particularly, to a kind of based on Demand Side Response of the sum of ranks than method Source value assessment method.
Background technology
All the time, people never stopped, and achieve good effect the research of Demand Side Response with practice. Understand that Demand Side Response resource has certain value by the practical experience of forefathers, this resource value refers to Demand Side Response Project application generated effect and influence in Operation of Electric Systems, the load including transfer, the capacity avoided, safety can Raising by property etc., fully considers effect and the influence of various aspects caused by Demand Side Response, and utilization is scientific and effective The behavior evaluated actual effect caused by Demand Side Response of method be known as Demand Side Response reserve value assessment.
At the early-stage to the research of Demand Side Response reserve value assessment at this stage, to Demand Side Response resource value phase It closes theory to be studied, needs to consider from many factors such as Generation Side, grid side, large user, resident, the whole society, structure Scientific and reasonable evaluation model is built to study Demand Side Response resource value.Have to the assessment of Demand Side Response resource value Help the decision of Demand Side Response project, the effect that supervision and check Demand Side Response is implemented works to Demand Side Response before It is assessed, the comparison of Demand Side Response implementation achievement between different cities.But be suitble to China's actual conditions, more comprehensively, The Demand Side Response reserve value assessment method of authority does not occur also.
Invention content
Method is compared based on sum of ranks it is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide a kind of Demand Side Response reserve value assessment method.
The purpose of the present invention can be achieved through the following technical solutions：
It is a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method, include the following steps：
S1, the evaluating matrix for establishing multiple multiple evaluation indexes for assessing objects；
S2, each assessment object corresponding to evaluation index each in evaluating matrix compile order, and the order of assessment object is calculated With than；
S3, the downward cumulative frequency that each assessment object is calculated simultaneously are converted into probability unit；
S4, using probability unit as independent variable, regression equation is established as dependent variable using the sum of ranks ratio for assessing object；
S5, grading sorting is carried out to assessment object according to regression equation, obtains evaluation result.
Preferably, the weight of evaluation index is obtained by Information Entropy in the evaluating matrix, specially：
Wherein, giRepresent the coefficient of variation of j-th of evaluation index, n represents the sum of evaluation index.
Preferably, the evaluation index includes profit evaluation model evaluation index and cost type evaluation index.
Preferably, each assessment object volume order corresponding to evaluation index each in evaluating matrix is specifically wrapped in the step S2 It includes：Profit evaluation model evaluation index compiles order from small to large, and cost type evaluation index then compiles order from big to small, if there are two or two with On evaluation object a certain evaluation index numerical value it is identical, then compile average order.
Preferably, the sum of ranks ratio of the assessment object is specially：
Wherein, wjRepresent the weight of j-th of evaluation index in evaluating matrix, RijRepresent j-th of i-th of assessment object The order of evaluation index.
Preferably, the downward cumulative frequency of the assessment object is specially：
Wherein,Represent each frequency grouping sum of ranks than rank range mean rank order, n represents the sum of evaluation index.
Preferably, the probability unit is specially：
Probiti=u (Pi)+5
Wherein, PiRepresent downward cumulative frequency, u (Pi) it is standard normal deviation function.
Compared with prior art, the present invention has the following advantages：
1st, index weights are considered on the basis of traditional RSR methods, effectively avoids the master that multifactor weight determines The property seen not only containing parametric statistics but also had had nonparametric statistics, can have been digested with numerous mathematical statistics methods.
2nd, this Demand Side Response reserve value assessment method can be not only quilt the Leakage in Value of Demand Side Response resource The sum of ranks ratio of object is assessed, grading sorting can also be carried out to the value of Demand Side Response resource, implementation result can be obtained Variation establishes solid foundation for later more deep development Demand Side Response related work.
3rd, the problem of particular values processing is difficult can be excluded with rank calculating, sum of ranks ratio dimensionless, integration capability is strong, Some special comprehensive indexes can be substituted, are calculated simply, it is easy to spread.
Specific embodiment
With reference to specific embodiment, the present invention is described in detail.The present embodiment is based on the technical solution of the present invention Implemented, give detailed embodiment and specific operating process, but protection scope of the present invention be not limited to it is following Embodiment.
Embodiment one
It is a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method, basic principle is：In a matrix, It is converted by order and obtains dimensionless statistic Wrsr, on this basis, with the distribution of Parameter statistical analysis technique study Wrsr, And good and bad directly sequence or the stepping of assessment object so as to make comprehensive assessment to object to be assessed, are calculated with Wrsr values Wrsr it is bigger, assessment object it is more excellent.This method includes the following steps：
S1, the evaluating matrix for establishing multiple multiple evaluation indexes for assessing objects；
S2, each assessment object corresponding to evaluation index each in evaluating matrix compile order, and the order of assessment object is calculated With than；
S3, the downward cumulative frequency that each assessment object is calculated simultaneously are converted into probability unit；
S4, using probability unit as independent variable, regression equation is established as dependent variable using the sum of ranks ratio for assessing object；
S5, grading sorting is carried out to assessment object according to regression equation, obtains evaluation result.
If assessment object has m, evaluation index has n, then j-th of index expression of i-th of assessment object is bij, structure Into evaluating matrix B=(bij)m×n, the weight of each evaluation index is obtained by Information Entropy in evaluating matrix, specially：
Wherein, giRepresent the coefficient of variation of j-th of evaluation index, specially：
gj=1-ej
Wherein, ejRepresent the entropy of j-th of evaluation index, specially：
Wherein, m represents the sum of assessment object, pijRepresent that j-th of evaluation index corresponds to the aspect ratio of i-th of assessment object Weight, 0<Pij<1, establishing criteria decision matrix calculates pij, specially：
Wherein, xijRepresent the index without dimension of j-th of evaluation index of i-th of assessment object, between evaluation index by It in property, unit, the difference of magnitude, needs to carry out standardization processing to it, obtains index without dimension square X=(xij)m×n, xijCalculation formula be：
Evaluation index includes profit evaluation model evaluation index and cost type evaluation index, and profit evaluation model evaluation index refers to that its numerical value is got over High better index, cost type evaluation index refer to the smaller the better index of its numerical value.
Each assessment object corresponding to evaluation index each in evaluating matrix is compiled order and is specifically included in step S2：Profit evaluation model is commented Estimate index and compile order from small to large, cost type evaluation index then compiles order from big to small, if there are two or it is more than two evaluation pair The a certain evaluation index numerical value of elephant is identical, then compiles average order, and obtained order matrix is denoted as R=(Rij)m×n。
Assessment object sum of ranks ratio be specially：
Wherein, wjRepresent the weight of j-th of evaluation index in evaluating matrix, RijRepresent j-th of i-th of assessment object The order of evaluation index.
Draw sum of ranks than frequency distribution table, list each class frequency fiAnd calculate each group cumulative frequencies ∑ fi, determine each group order With than rank range R mean rank orderThe downward cumulative frequency of assessment object is calculated according to the following formula：
The P that will be obtainediIt is converted into the probability unit Probiti of i-th of assessment object：
Probiti=u (Pi)+5
Wherein, PiRepresent downward cumulative frequency, u (Pi) it is standard normal deviation function.
Step S4 is using the probability unit Probiti corresponding to cumulative frequency as independent variable, with i-th of assessment object Wrsr For dependent variable, the regression equation of foundation is：
Wrsr=a+b × Probiti
Wherein, a and b is coefficient.
The present embodiment obtains the 2nd row and the 2nd row pair in percentage and the control value of probability unit, such as table 1 by table 1 Answer percentage and be 11%, infall 3.77 is then corresponding probability unit.
1 percentage of table and the probability unit table of comparisons
The Wrsr corresponding to regression equation calculation according to obtained by the above method carries out grading sorting to assessment object.No It is as shown in table 2 with the corresponding probability unit Probit values of gear number.It is unanimously best Grading Principle of Rated to adhere to each shelves variance, according to reality Situation determines specific stepping number, and after determining stepping number, probability unit Probit critical values are substituted into equation of linear regression calculating pair The Wrsr answered, so as to obtain assessment object grading sorting situation.
Table 2 often uses the critical value of stepping situation probability unit
Demand Side Response value evaluation of tourism resources is on the basis of single index is analyzed, and considers multinomial evaluation index, Demand Side Response reserve value assessment index system is formed, and then obtains the process of its examination value, taking the form of as a result needs Seek the overall target or grade of side resource response value.
Demand Side Response resource value class boundaries value has certain randomness and ambiguity, i.e. Demand Side Response resource Value assessment is divided into overall target quantitative evaluation according to result and grade is assessed.Quantitative evaluation is by each Demand Side Response resource Value index carries out numeralization calculating, and assessment result is specific numerical value.Grade is assessed, it is thus necessary to determine that Demand Side Response provides Source is worth stepping number and boundary value, then judges the grade residing for object to be assessed.In Demand Side Response value evaluation of tourism resources Index concrete numerical value Wrsr can not only have been obtained, but also can carry out grade to assessment result stepping and comment using the method that the application proposes Estimate.
When working out Demand Side Response resource value index, differentiation index is needed to belong to cost type or profit evaluation model. Such as it is profit evaluation model index that can avoid peak demand capacity cost, can avoid the indexs amount such as fuel cost, compiles order, numerical value from big to small Bigger rank is higher；Similarly, the indexs such as the power selling income of reduction, equipment investment of early period be cost type index, to its into During row establishment, the bigger rank of numerical value is smaller, when establishment, with reference to correlation analysis and international standard between index, accomplishes as possible Rationally.
Embodiment two
2009 to the 2013 years data implemented after Demand Side Response in somewhere, as shown in table 3.Referred to according to index matrix calculating Target weight is [0.0235 0.0049 0.0517 0.0039 0.008 0.0019 0.0522 0.0035 0.0815 0.0006 0.0026 0.0016 0.3584 0.0128 0.1504 0.0015 0.0139 0.0926 0.0063 0.0238 0.0383 0.0476 0.0021 0.0025 0.0105 0.0035].The indices in time each in initial data are carried out Establishment, the results are shown in Table 4 for establishment, the Wrsr in each time is calculated according to formula, as shown in table 5.
3 initial data of table
The rank of 4 each index of table
The weighting sum of ranks ratio in 5 each time of table
Time 2009 2010 2011 2012 2013
Wrsr 0.416 0.542 0.615 0.637 0.791
It may determine that by Wrsr values, Demand Side Response implementation result 2013>2012>2011>2010>2009, it is known that need Response implementation implementation result is asked to improve year by year, the best time is 2013, and specific grade divides as shown in table 6.
6 grade classification of table
Equation of linear regression is calculated using least square method, using the probability unit Probit corresponding to cumulative frequency as change certainly Amount, using Wrsr as dependent variable, the regression equation that acquires：
Wrsr=0.14Probit-0.1461
Grading sorting is unanimously the principle of best stepping according to stepping variance, is divided into outstanding, good, general third gear, stepping The results are shown in Table 7, by grading sorting result in table 7 as it can be seen that demand response in 2013 is outstanding, 2009,2010,2011, 2012 are good, it follows that the performance of nearly 5 years Demand Side Responses since two thousand nine is become better and better, and And when 2013, implementation result improvement of getting married and start a new life becomes outstanding, realizes fundamental change.
7 grading sorting of table
Grade Probit Wrsr Grading sorting
Generally <4 <0.4139 Nothing
Well [4,6] [0.4139,0.6939] 2009、2010、2011、2012
It is outstanding >6 >0.6939 2013
It can obtain through this embodiment, in Demand Side Response value evaluation of tourism resources problem, this method is suitable for demand Side resource response value assessment.This method considered on the basis of traditional RSR methods index weights effectively avoid mostly because The subjectivity that plain weight determines not only can also may be used the Wrsr that the Leakage in Value of Demand Side Response resource is evaluation object To carry out grading sorting to the value of Demand Side Response resource.The present embodiment it is found that Demand Side Response China implementation result Improve year by year, while also demonstrate that the value of Demand Side Response Jiyuan can not be ignored, for later more deep development Demand-side Response related work establishes solid foundation.

Claims (7)

  1. It is 1. a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method, which is characterized in that include the following steps：
    S1, the evaluating matrix for establishing multiple multiple evaluation indexes for assessing objects；
    S2, each assessment object corresponding to evaluation index each in evaluating matrix compile order, and the sum of ranks ratio of assessment object is calculated；
    S3, the downward cumulative frequency that each assessment object is calculated simultaneously are converted into probability unit；
    S4, using probability unit as independent variable, regression equation is established as dependent variable using the sum of ranks ratio for assessing object；
    S5, grading sorting is carried out to assessment object according to regression equation, obtains evaluation result.
  2. It is 2. according to claim 1 a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method, feature It is, the weight of evaluation index is obtained by Information Entropy in the evaluating matrix, specially：
    Wherein, giRepresent the coefficient of variation of j-th of evaluation index, n represents the sum of evaluation index.
  3. It is 3. according to claim 1 a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method, feature It is, the evaluation index includes profit evaluation model evaluation index and cost type evaluation index.
  4. It is 4. according to claim 3 a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method, feature It is, each assessment object corresponding to evaluation index each in evaluating matrix is compiled order and specifically included in the step S2：Profit evaluation model Evaluation index compiles order from small to large, and cost type evaluation index then compiles order from big to small, if there are two or more than two evaluations The a certain evaluation index numerical value of object is identical, then compiles average order.
  5. It is 5. according to claim 1 a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method, feature It is, the sum of ranks ratio of the assessment object is specially：
    Wherein, wjRepresent the weight of j-th of evaluation index in evaluating matrix, RijRepresent that j-th of assessment of i-th of assessment object refers to Target order.
  6. It is 6. according to claim 1 a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method, feature It is, the downward cumulative frequency of the assessment object is specially：
    Wherein,Represent each frequency grouping sum of ranks than rank range mean rank order, n represents the sum of evaluation index.
  7. It is 7. according to claim 6 a kind of based on Demand Side Response reserve value assessment method of the sum of ranks than method, feature It is, the probability unit is specially：
    Probiti=u (Pi)+5
    Wherein, PiRepresent downward cumulative frequency, u (Pi) it is standard normal deviation function.
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112734221A (en) * 2021-01-06 2021-04-30 安徽易测评信息技术有限公司 Statistical calculation method for estimating task quantity of each responsibility unit based on civilized city assessment item
CN112990673A (en) * 2021-02-26 2021-06-18 国网河北省电力有限公司 Distribution network distribution area operation state evaluation monitoring method based on rank-sum ratio method
CN113393099A (en) * 2021-05-31 2021-09-14 国网河北省电力有限公司经济技术研究院 Power distribution network project group value index evaluation method and device and terminal equipment
CN114638556A (en) * 2022-05-18 2022-06-17 成都唐源电气股份有限公司 Contact network quality evaluation method based on weighted rank-sum ratio algorithm
CN117764454A (en) * 2023-12-27 2024-03-26 兰州理工大学 Evaluation method for development degree of flaky stripping of wall site in open great wall of Hexi corridor

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020061835A1 (en) * 1997-08-28 2002-05-23 Kensey Kenneth R. In vivo delivery methods and compositions
CN103106790A (en) * 2013-01-16 2013-05-15 东南大学 Plane intersection design variable weight comprehensive evaluation method based on rank sum ratio method
CN104616212A (en) * 2015-02-06 2015-05-13 广东电网有限责任公司电力调度控制中心 Relay protection system reliability analysis method and system
CN106327106A (en) * 2016-09-13 2017-01-11 国网河北省电力公司 Demand side response resource value evaluation method based on rough set theory
CN107169633A (en) * 2017-04-20 2017-09-15 中石化石油工程技术服务有限公司 A kind of gas line network, gas storage peak regulating plan integrated evaluating method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020061835A1 (en) * 1997-08-28 2002-05-23 Kensey Kenneth R. In vivo delivery methods and compositions
CN103106790A (en) * 2013-01-16 2013-05-15 东南大学 Plane intersection design variable weight comprehensive evaluation method based on rank sum ratio method
CN104616212A (en) * 2015-02-06 2015-05-13 广东电网有限责任公司电力调度控制中心 Relay protection system reliability analysis method and system
CN106327106A (en) * 2016-09-13 2017-01-11 国网河北省电力公司 Demand side response resource value evaluation method based on rough set theory
CN107169633A (en) * 2017-04-20 2017-09-15 中石化石油工程技术服务有限公司 A kind of gas line network, gas storage peak regulating plan integrated evaluating method

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112734221A (en) * 2021-01-06 2021-04-30 安徽易测评信息技术有限公司 Statistical calculation method for estimating task quantity of each responsibility unit based on civilized city assessment item
CN112990673A (en) * 2021-02-26 2021-06-18 国网河北省电力有限公司 Distribution network distribution area operation state evaluation monitoring method based on rank-sum ratio method
CN113393099A (en) * 2021-05-31 2021-09-14 国网河北省电力有限公司经济技术研究院 Power distribution network project group value index evaluation method and device and terminal equipment
CN114638556A (en) * 2022-05-18 2022-06-17 成都唐源电气股份有限公司 Contact network quality evaluation method based on weighted rank-sum ratio algorithm
CN114638556B (en) * 2022-05-18 2022-08-16 成都唐源电气股份有限公司 Contact network quality evaluation method based on weighted rank-sum ratio algorithm
CN117764454A (en) * 2023-12-27 2024-03-26 兰州理工大学 Evaluation method for development degree of flaky stripping of wall site in open great wall of Hexi corridor

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